Secondly, companies need to realize that they request multiple programming languages because the current programming languages can't parse stack traces, and they push everything to microservices, so they can parse their errors from DevOps services. Which means they don't request only to know multiple languages, but also DevOps services.
I have written about all these in a previous article of mine https://rm4n0s.github.io/posts/5-it-will-take-your-job
in the article I wrote how detrimental it is to the developer's social life, to know multiple languages.
That is an opinion and not fact. One based on your personal experience that is not universal in any way. Knowing multiple programming languages is quite normal and I would expect any good software developer to pick and up be able to program in (almost) any language. I guess https://en.wikipedia.org/wiki/Brainfuck might be an exception. JCL comes close to it.We learned this in high school and it was super fun: https://en.wikipedia.org/wiki/Busy_beaver
Do I expect everyone to be an instant expert in any language? Or able to create the busiest beaver? No of course not! But I do expect any decent programmer to pick up any programming language and work in it.
Do we all have preferences? Heck yes! I absolutely dislike Python and would not take a job where I have to program in it if I wasn't forced to by circumstances. I've never done C# or Lua professionally but it was super easy to pick both up when I dabbled with them for game development in private (each respective game engine used these languages for scripting).
Secondly, companies need to realize that they request multiple programming languages because the current programming languages can't parse stack traces
I read something like that in the article and it still makes no sense whatsoever when I read it here either. Parsing a stack trace in various languages is absolutely possible. But what's that got to do with anything?FWIW, yes, I've actually looked at previous stack frames (e.g. `e.getCause()` in Java) for error handling. It always felt very very dirty but it was my only choice under the circumstances.
they push everything to microservices
We have to distinguish the why there.Some companies (meaning the people within those companies) because they read about how Netflix has x-many of them and it's the thing to do today. Stay away from those companies. They will also make you do other things just because someone read an article of forbes.com.
And then there's companies that are actually trying to solve similar problems as the ones that Netflix was trying to solve with microservices and it actually makes sense to model their internal application service landscape that way! We're in that space for example. We have one big legacy "macroservice" aka very monolithic core and then we have a bunch of newer microservices (some larger, some smaller) that actually solve problems. All of these microservices are written in exactly two languages: Java and Kotlin. Newer ones in Kotlin, older ones in Java (like the legacy monolith). The FE is written in exactly one language by now: Typescript (converted from quite a large javascript code base over multiple years).
so they can parse their errors from DevOps services
What does that even mean? Makes no sense to me whatsoever. If you're talking about having a central log analytics service like Splunk, Datadog or Graylog et al. then that has nothing to do with microservices or multiple languages. At a previous place we had a bunch of monoliths make up the overall application and splunk so that you'd be able to actually reason about what the system overall was doing for any given overall user transaction / session and it was awesome to have. And if you have any sort of actual need to run software that has uptime requirements, then you are going to run at least two replicas of whatever service you created, monolith or not and you want a central log aggregation service.I'm really sorry to say this, but it seems like your articles are really just ranting about things that you personally don't like for one reason or another but there's no actual real reasoning or universal truth to it.
When you try to implement it, then everything on what I said will make sense to you.
Also, we don't need log systems when there is a programming language like Odin to parse stack traces with type checking (not just string like you gave me as an example from Java).
In microservices you are the error handlers. For example, if in the logs you see a stack trace, then you will go to the code and fix the error.
In Odin I don't need to go in that trouble, because ALL the stack traces can be handled. There will be no undefined behavior in software or unexpected input that caused an unexpected stack trace, so there is no reason to have logs.
Let's say you have the call stack as this (from your example):
f4()->
f3()->
f1()->
ErrInvestmentLost
Great, I'll handle this based on the fact that f1 was called by f3 (in the Java example, you'll just inspect e.getCause() until you reach the desired point in the trace - basically do what `printStackTrace()` but don't print it and instead do your error handling based on it).But nobody would ever want to do this because it's super brittle. I change f4 so that it first calls f17, which then calls f3, which then calls f17 again, which calls f1 and your error handling based on the call path is suddenly broken.
What is it that you are trying to even achieve by doing this? Proper error handling doesn't depend on the call path. Proper error handling depends on the type of error that occurred and whether you can actually handle it at all or if you just have to give up and throw the error all the way to where it will get logged for a programmer to take a look at why it happened and why we couldn't handle it.
Your claim about being able to handle "all stack traces" makes no sense to me. You don't handle stack traces. You handle error types.
A real world example of the above (taking Java as an example again) might be a REST resource. My error handling should not depend on nor suddenly break, just because someone configured a new filter in the filter chain that sits above the actual resource method. Say someone added in a `AuthenticationFilter` that checks if some auth token is present and valid and that didn't used to be the case. Now any error handling in my resource method that was based on the exact stack trace combination that existed before that filter was added will break horribly.
Your system with Java will break if someone else add an AuthenticationFilter, but my system in Odin will not even compile until I have handled all the stack trace paths that include AuthenticationFilter.
Do you see the differences between handling stack traces with union types rather than string?
See, the `AuthenticationFilter` sits outside of my REST resource. I could not care less that someone configured it and that at runtime, based on some configuration that can change without even needing a recompilation, this filter will either be there on the stack or it won't.
My resource does not interact with this filter in any way and when an error happens somewhere down in another method I call, then I don't care that I was called with or without the auth token having been checked by said filter. I might care whether the method I called threw a `SQLException` or a `JSONParseException` but very probably I don't even care about that at all because I can't do anything specific in either case and will just throw it further (i.e. not handle it, other than potentially logging it).
Java actually tried the whole "specify all error situations with checked exceptions and otherwise the code won't even compile" and it failed miserably and you are hard pressed to see anything new derive from `Exception`. Everyone uses `RuntimeException`. It does come at a cost, because now I no longer have the hassle of explicitly knowing and deciding what to do with these exceptions and I may only figure out that a particular type of error can happen once I "see it in the wild" (e.g. in my logs, coz something failed) or I'm lucky enough to have actually read the documentation and handled all the exceptions I wanted to handle.
But that happened precisely because it was just too much to have all your code specify these exceptions when everyone figured out that 99% of all code just threw them further up the stack. You call one new library method that specifies an exception and you suddenly have to adjust 127 other files and the only thing you do is to declare all those methods will also just throw the exception further up the stack.
For example, in Authentication_Filter_Error union, you will have another union called SQL_Verify_Account_Error, that it will contain SQL_Error enum with the Closed_Conn value.
Imagine your stack trace like this Authentication_Filter_Error -> SQL_Verify_Account_Error -> SQL_Error.Closed_Conn
Now when you know that can happen (through CDD), you can create a switch statement to catch the specific stack trace, to call the system administrator in the middle of the night to check what happens.
This is how software should handle its errors and there is not even a need to log it.
In your scenario, you wake up, you go to work, everyone is screaming at the office, you check the logs, you see the problem, and then you call the system administrator for the problem.
However, that's still about the exceptions thrown from down thread, not from the call path part of the "stack trace".
I.e. your situation would never happen.
Authentication_Filter_Error -> SQL_Verify_Account_Error -> SQL_Error.Closed_Conn
This stack / call path is impossible, because when the AuthenticationFilter notices that the token is invalid, it returns a 401 or 403 or whatever is appropriate and my REST resource is never actually called. There's no SQL being run and very definitely no "connection closed" error occurred.But let's say there was a distinction made with proper exception types and instead of `SQLException("Connection closed")` and `SQLException("Statement timeout")`, I actually received `SQLException(ConnectionClosedException())` vs. `SQLStatementTimeoutException`. Now, without string parsing, I can know that either the connection just closed or that the statement was aborted due to timeout. If these are checked exceptions, I have to declare that I'm aware these can happen and what I want to do with them: Handle or rethrow.
However, a myriad of such exceptions can happen. I would probably have to declare 20-50 exceptions way up in a REST resource layer. Not only can these two happen, but many other situations on the network or database side and on the JSON parsing side for the payload I receive, some exceptions from my business logic etc.
And for most of these, what can I do? If the connection to the database closed, all I can do is to log the error and return a `500 Internal Server Error` to my caller. Guess what I can do when a statement timeout occurs? I log the error and return a `500 Internal Server Error` to my caller. For a statement timeout I can't even return a `400 Bad Request`, because it's not knowable if the statement timeout occurred because the database was simply overloaded in that moment or if the request itself was created with such parameters as to always cause a statement timeout. Until we see the logs and through investigation figure out that it wasn't a bad request after all anyway. We were missing an index and the table finally grew large enough for that to matter.
So yeah, I'm good with `RuntimeException` and handling only very few specific ones ever.
Also nobody will be screaming when the token is invalid and I definitely don't call any system administrator. That's something you as a developer look into. Same with the statement timeout.
You could make the software call the system administrator and return a message to the user "Try again in an hour, the system administrator is fixing it now"
Or if it is a timeout, the software will call amazon to buy a new machine to scale the database and send a message to the user "Try again in an hour until we scale the system".
Developer's job is to automate error handlers and not be the error handlers.
If you can see the stack trace tree, then you can plan far ahead, but to do that we need to destroy this "agile" mindset, that is always in a hurry and doesn't let you to think that far ahead.
you can make the software to handle these kind of errors.
No you can not do this in all cases and I described multiple cases in my comment already in which you can't reasonably do anything automatic. Let me explain. You could make the software call the system administrator
But why would I do that for every `StatementTimeoutException` at every moment of the night and why do I need to bake that into my error handling? That isn't actually handling the error. "Try again in an hour, the system administrator is fixing it now"
Please never ever do this to either your users, who may believe it or you "system administrators" who do value their sleep or have other more pressing matters to attend to. Or if it is a timeout, the software will call amazon to buy a new machine to scale the database
I described a case in which automatically adding resources would actually be wrong in that it would completely mask the actual problem, which is that the developer did not think about the access patterns of the software they wrote enough and did not add the right index to the database. If you keep scaling your database automagically you'll pay AWS until you run out of money and have not solved anything. Believe me, a missing index can eat up a lot of resources before anything gets better. And until then your software will just keep failing and keep adding resources. And in this case it won't help at all because your new machine will not even be used by the query. It'll still only be one node handling your read and that is constrained by actually reading data from the disk and that's super slow because you forgot the index! Developer's job is to automate error handlers and not be the error handlers.
I've yet to see anything that the developer should do here based on an individual error in the software. One case where something should happen automatically on the database would be if the database was running out of space. You should have monitoring in place that takes care of that. And no it should not be your software doing that scaling because it received a `SQLError -> DatabaseOutOfDiskSpace` error. If it gets that far, all of your calls to the database will fail. Which of your error handlers should be the one handling it and why should we let things get that far in the first place? Have monitoring set up outside of your actual software that adds disk space automatically before you run out of space and then make it scream very loudly to your system administrators and developers about it, so that they can take a look at it and determine if this was a legitimate "well I guess we got too many more paying customers now, this was OK" or if it was the last update that went out having a bug that keeps filling up the database with BS data and you need to make an emergency bug fix or maybe you're deliberately being DDoS'd and it got past your DDoS protection and you better do something about that or the DDoS'er is gonna make your AWS bill go crazy. If you can see the stack trace tree
Again, nothing and nobody cares about up-stack. I care about down-stack when handling such errors. we need to destroy this "agile" mindset, that is always in a hurry and doesn't let you to think that far ahead.
Nothing to do with agile at all. You should think about error handling every time you code anything. For example as we've seen above, think ahead about your database running out of disk space. But don't make every developer think about it for every single piece of code they ever write. That makes no sense to have them try to handle these situations. It'd actually make it worse and these people would never get any actual work done either.Ask your boss, "do you want your users wait until the next morning for the system administrator to wake up and fix the issue? Or do you want the software inform the user how long it will take to fix the issue in seconds and start calling the system administrator to wake up and fix it?"
Because you answer based on your preferences as a worker who wants to avoid the extra work to make the system perfect and not your boss's preferences.
And yes, there's an on-call person that does get paged when something happens that likely needs immediate attention. A page for every single time there's any error? Not bloody likely mate.
To pick up your last point: My boss is not in the business of paying for you, who will spend countless extra days building useless error "handling" for stuff that has already been handled and who is trying to get out of the responsibility of writing resilient software by paging someone else to "pick up the tab".
A "boss" never wants to pay for a perfect system. That would take way too long and nobody has figured out how to actually build that anyway (no, Odin is not the answer). They want to pay for the "slightly less than good enough" system, because that's cheaper and still gets the job done. And especially when I hear you talk here, I'm with them: Perfect is the enemy of good enough. We just have to ensure that it really is good enough and not less (coz many a boss will happily take way less than good enough if it gets them to market faster.